Recommended Prerequisites

The student should have knowledge on Cell and Molecular Biology and Mathematics corresponding to the 1st and 2nd year of the Integrated Master. The student should be able to read and understand papers or other bibliography in English.

Teaching Methods

- Theoretical classes: 15 h

- Theoretical/Practical classes: 30 h:

- discussion of scientific papers and different topics of genomics with students;

- interaction with different genomic methodologies in the lab;

- resolution of problem-cases with different bioinformatics tools

- Tutorial: 10 h

- guidance in the resolution of case-problems, scientific papers and topics discussion

Learning Outcomes

Understand the genome and its specifications.

Understand the importance of Genomics, the science that analyses and compares complete genomes or a large set of genes simultaneously, in different fields, namely in the field of medicine.

Evaluate and identify the different technological tools in the field of genomics, understanding its limitations and possibilities.

Identify, evaluate and understand data bases and bioinformatic tools for the analysis of multiple data, in the field of genomics.

Identify and understand the importance and the application of different technologies and tools for data analysis in emergent fields like pharmacogenomics, nutrigenomics, toxicogenomics and metagenomics.

Delineate strategies and approaches to data analysis in genomics.

Discuss ethical and regulatory issues related with data analysis and interpretation in the field of genomics.

Work Placement(s)

No

Syllabus

Basic concepts in Genetics

- DNA, genes and chromosomes

- Mutations and chromosomal abnormalities

- Gene expression and its regulation

- Genetic variability

Structural Genomics

- Technologies and tools

- Genomes mapping and genomic annotation

- HapMap Project

- Structural Genomics - data bases and bioinformatic tools

Functional Genomics

- Encode Project

- Correlation of Genomics with Transcriptomics, Proteomics, Metabonomics and Lipidomics

- Technologies

- Functional Genomics - data bases and bioinformatic tools

Comparative Genomics and evolution

- Variation of different genomes - human genome and genomes of some animal models

- Metagenomics and its applications

- Comparative Genomics - data bases and bioinformatic tools

Genomics and Medicine

- Genomics in clinical diagnosis, personal identification and forensic research